Machine Learning Approach for Online Monitoring of Quality of Transmission Performance Indicators in Optical Fiber Networks

We propose online monitoring of quality of transmission (QoT) in optical fiber networks aided by machine learning. Three regression models were comparatively fitted to estimate the current and long-term QoT indicators. Real data from on-line measurable, equipment-agnostic features was provided through realistic network experimental scenarios.

Automated summary

This study suggests online monitoring of optical fiber network transmission quality using machine learning, fitting three regression models to estimate current and long-term QoT indicators, and providing real data from online measurable, equipment-agnostic features through realistic network experimental scenarios.